Jeremy H. M. Wong

Orcid: 0000-0003-3742-7510

According to our database1, Jeremy H. M. Wong authored at least 23 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2024
Dataset-Distillation Generative Model for Speech Emotion Recognition.
CoRR, 2024

Distilling Distributional Uncertainty from a Gaussian Process.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Modelling Inter-Rater Uncertainty in Spoken Language Assessment.
IEEE ACM Trans. Audio Speech Lang. Process., 2023

Noise robust distillation of self-supervised speech models via correlation metrics.
CoRR, 2023

Multiple output samples for each input in a single-output Gaussian process.
CoRR, 2023

Distilling knowledge from Gaussian process teacher to neural network student.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

Variational Gaussian Process Data Uncertainty.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2023

2022
Joint Speaker Diarisation and Tracking in Switching State-Space Model.
Proceedings of the IEEE Spoken Language Technology Workshop, 2022

Diarisation Using Location Tracking with Agglomerative Clustering.
Proceedings of the IEEE Spoken Language Technology Workshop, 2022

Variations of multi-task learning for spoken language assessment.
Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

2021
Hidden Markov Model Diarisation with Speaker Location Information.
Proceedings of the IEEE International Conference on Acoustics, 2021

Ensemble Combination between Different Time Segmentations.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
Combination of End-to-End and Hybrid Models for Speech Recognition.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

High-Accuracy and Low-Latency Speech Recognition with Two-Head Contextual Layer Trajectory LSTM Model.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Ensemble generation and compression for speech recognition
PhD thesis, 2019

General Sequence Teacher-Student Learning.
IEEE ACM Trans. Audio Speech Lang. Process., 2019

Exploiting Future Word Contexts in Neural Network Language Models for Speech Recognition.
IEEE ACM Trans. Audio Speech Lang. Process., 2019

Learning Between Different Teacher and Student Models in ASR.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2019

2018
Sequence Teacher-Student Training of Acoustic Models for Automatic Free Speaking Language Assessment.
Proceedings of the 2018 IEEE Spoken Language Technology Workshop, 2018

Phonetic and Graphemic Systems for Multi-Genre Broadcast Transcription.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017
Student-Teacher Training with Diverse Decision Tree Ensembles.
Proceedings of the 18th Annual Conference of the International Speech Communication Association, 2017

Multi-task ensembles with teacher-student training.
Proceedings of the 2017 IEEE Automatic Speech Recognition and Understanding Workshop, 2017

2016
Sequence Student-Teacher Training of Deep Neural Networks.
Proceedings of the 17th Annual Conference of the International Speech Communication Association, 2016


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